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Quantitative Finance > Risk Management

Title:
Bitcoin Risk Modeling with Blockchain Graphs

Abstract: A key challenge for Bitcoin cryptocurrency holders, such as startups using
ICOs to raise funding, is managing their FX risk. Specifically, a misinformed
decision to convert Bitcoin to fiat currency could, by itself, cost USD
millions.
In contrast to financial exchanges, Blockchain based crypto-currencies expose
the entire transaction history to the public. By processing all transactions,
we model the network with a high fidelity graph so that it is possible to
characterize how the flow of information in the network evolves over time. We
demonstrate how this data representation permits a new form of microstructure
modeling - with the emphasis on the topological network structures to study the
role of users, entities and their interactions in formation and dynamics of
crypto-currency investment risk. In particular, we identify certain sub-graphs
('chainlets') that exhibit predictive influence on Bitcoin price and
volatility, and characterize the types of chainlets that signify extreme
losses.